Deep LDA.
Fisher linear discriminant analysis [1]} is a classical means of tackling classification,
which relies on finding projections that minimise intra-class variance (i.e., pull together projected scores) and maximise inter-class variance (i.e., push apart projected scores).
In a deep learning context, [2]} proposed a form of deep LDA.
This is not attuned to the long-tail setting, and does not enforce classification or embedding margins.
